Update to ndarray 0.16

.github/workflows/ci.yml

@@ -20,14 +20,16 @@ jobs:
           - stable
           - beta
           - nightly
-          - 1.49.0  # MSRV
+          - 1.64.0  # MSRV
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions-rs/toolchain@v1
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
         with:
-          profile: minimal
           toolchain: ${{ matrix.rust }}
-          override: true
+      - name: Pin versions for MSRV
+        if: "${{ matrix.rust == '1.64.0' }}"
+        run: |
+          cargo update -p regex --precise 1.8.4
       - name: Build
         run: cargo build --verbose
       - name: Run tests
@@ -40,21 +42,16 @@ jobs:
         include:
           # 64-bit, big-endian
           - rust: stable
-            target: mips64-unknown-linux-gnuabi64
-          # 32-bit, big-endian
-          - rust: stable
-            target: mips-unknown-linux-gnu
+            target: s390x-unknown-linux-gnu
           # 32-bit, little-endian
           - rust: stable
             target: i686-unknown-linux-gnu
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions-rs/toolchain@v1
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
         with:
-          profile: minimal
           toolchain: ${{ matrix.rust }}
           target: ${{ matrix.target }}
-          override: true
       - name: Install cross
         run: cargo install cross -f
       - name: Build
@@ -86,12 +83,10 @@ jobs:
         rust:
           - nightly
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions-rs/toolchain@v1
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
         with:
-          profile: minimal
           toolchain: ${{ matrix.rust }}
-          override: true
       - name: Install tarpaulin
         run: cargo install cargo-tarpaulin -f
       - name: Generate code coverage

Cargo.toml

@@ -16,7 +16,7 @@ keywords = ["array", "multidimensional", "statistics", "matrix", "ndarray"]
 categories = ["data-structures", "science"]
 
 [dependencies]
-ndarray = "0.15.0"
+ndarray = "0.16.0"
 noisy_float = "0.2.0"
 num-integer = "0.1"
 num-traits = "0.2"
@@ -25,11 +25,11 @@ itertools = { version = "0.10.0", default-features = false }
 indexmap = "1.6.2"
 
 [dev-dependencies]
-ndarray = { version = "0.15.0", features = ["approx"] }
+ndarray = { version = "0.16.1", features = ["approx"] }
 criterion = "0.3"
 quickcheck = { version = "0.9.2", default-features = false }
-ndarray-rand = "0.14.0"
-approx = "0.4"
+ndarray-rand = "0.15.0"
+approx = "0.5"
 quickcheck_macros = "1.0.0"
 num-bigint = "0.4.0"
 

tests/summary_statistics.rs

@@ -164,7 +164,7 @@ fn test_with_array_of_floats() {
         epsilon = 1e-12
     );
 
-    let data = a.into_shape((2, 5, 5)).unwrap();
+    let data = a.into_shape_with_order((2, 5, 5)).unwrap();
     let weights = array![0.1, 0.5, 0.25, 0.15, 0.2];
     assert_abs_diff_eq!(
         data.weighted_mean_axis(Axis(1), &weights).unwrap(),
@@ -254,7 +254,9 @@ fn mean_axis_eq_if_uniform_weights() {
         let depth = a.len() / 12;
         a.truncate(depth * 3 * 4);
         let weights = Array1::from_elem(depth, 1.0 / depth as f64);
-        let a = Array1::from(a).into_shape((depth, 3, 4)).unwrap();
+        let a = Array1::from(a)
+            .into_shape_with_order((depth, 3, 4))
+            .unwrap();
         let ma = a.mean_axis(Axis(0)).unwrap();
         let wm = a.weighted_mean_axis(Axis(0), &weights).unwrap();
         let ws = a.weighted_sum_axis(Axis(0), &weights).unwrap();
@@ -288,7 +290,9 @@ fn weighted_var_algo_eq_simple_algo() {
         }
         let depth = a.len() / 12;
         a.truncate(depth * 3 * 4);
-        let a = Array1::from(a).into_shape((depth, 3, 4)).unwrap();
+        let a = Array1::from(a)
+            .into_shape_with_order((depth, 3, 4))
+            .unwrap();
         let mut success = true;
         for axis in 0..3 {
             let axis = Axis(axis);